Proposition of extension of models relating rheological quantities and microscopic structure through the use of a double fractal structure

Bouthier, Louis-Vincent; Castellani, Romain; Hachem, Elie; Valette, Rudy

doi:10.1063/5.0101750

Cited by 5 publications

(10 citation statements)

References 40 publications

(47 reference statements)

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“…The same theoretical approach has also been used to derive mathematical equations to describe the plastic behavior of colloidal fractal gels (Bouthier et al, 2022). These equations are typically based on an analysis of the force required to disrupt the bonds between the structural elements in the gel (Mewis & Wagner, 2012).…”

Section: Polymer Matricesmentioning

confidence: 99%

“…, where ϕ eff and ϕ F are the effective volume fraction and actual volume fraction of the flocs in the system (Bouthier et al, 2022). By accounting for the fact that the flocs are occupied by particles, a critical particle volume fraction (ϕ crit ) for percolation can be obtained:…”

Section: Polymer Matricesmentioning

confidence: 99%

“…In this section, a theoretical model recently developed to describe the rheology of colloidal suspensions containing aggregated spherical particles assembled into fractal structures is considered (Bouthier et al, 2022). This model assumes that the rheological properties of the colloidal suspensions can be related to their microstructure by assuming that the individual particles are assembled into flocs with a fractal structure, and that these flocs then aggregate with each other to form a network with another fractal structure (Figure 11).…”

Section: Modeling Of Rheological Properties Of Solid‐like Plant‐based...mentioning

confidence: 99%

“…Here, U is the interaction potential between a pair of aggregated particles, a is the diameter of the individual particles, δ is the distance between a pair of aggregated particles, ϕ is the volume fraction of the particles present in the overall system, l is the diameter of the flocs, D P is the fractal dimension of the particles inside the flocs, d P is the fractal dimension (from 1.1 to 1.4) of the elastic backbone inside the flocs (i.e., the load bearing particles), D F is the fractal dimension of the aggregated flocs in the overall system, and d F is the fractal dimension (from 1.1 to 1.4) of the elastic backbone of the aggregated flocs in the overall system (i.e., the load bearing flocs). The function in this equation, f( x ), is related to the relative strength of the interactions between the particles compared to the flocs, as well as to the degree of bending or stretching experienced by the load bearing units (Bouthier et al, 2022):

normalf ((), x) goodbreak= α ((), 2 ε goodbreak+ x) goodbreak- 1 .

…”

Section: Modeling Of Rheological Properties Of Solid‐like Plant‐based...mentioning

confidence: 99%

“…The above equations will only be valid when the flocs form a network that occupies the entire volume of the system, which will occur when the percolation threshold is exceeded. To a first approximation, this concentration can be obtained from the following equation:

ϕ_{eff} goodbreak= ϕ_{F} {(l / a)}^{3 - D_{F}} goodbreak= 1

, where ϕ eff and ϕ F are the effective volume fraction and actual volume fraction of the flocs in the system (Bouthier et al, 2022). By accounting for the fact that the flocs are occupied by particles, a critical particle volume fraction ( ϕ crit ) for percolation can be obtained:

ϕ_{crit} goodbreak= {(a / l)}^{6 - D_{F} goodbreak- D_{P}}

…”

Section: Modeling Of Rheological Properties Of Solid‐like Plant‐based...mentioning

confidence: 99%

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Modeling the rheological properties of plant‐based foods: Soft matter physics principles

2023

Sustainable Food Proteins

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There is growing interest in the design and fabrication of next‐generation plant‐based (NG‐PB) foods that have physicochemical and functional properties that simulate those of traditional animal‐based foods, like meat, seafood, egg, and dairy products. Many of these products are colloidal materials containing particles or polymers, which means that their properties can be understood using soft matter physics concepts. The rheological properties of NG‐PB foods may vary widely, including low‐viscosity fluids (like milk), high‐viscosity fluids (creams), soft solids (like yogurt), and hard solids (like some cheeses). For manufacturers of NG‐PB foods to mimic this broad range of products it is important to have theoretical models to identify, predict, and control the key parameters impacting their textural attributes. In this article, the theoretical models developed to describe the properties of fluid, semi‐solid, and solid colloidal dispersions are summarized, and their potential for improving the design and fabrication of NG‐PB foods is highlighted. In the future, it will be important to establish the most appropriate models for different categories of NG‐PB foods and to determine their range of applications.

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Section: Polymer Matricesmentioning

confidence: 99%

Section: Polymer Matricesmentioning

confidence: 99%

Section: Modeling Of Rheological Properties Of Solid‐like Plant‐based...mentioning

confidence: 99%